Comments (6)
You can set these hyper-parameter similar to how you train a normal/uncompressed model on your own data set, without PocketFlow.
from pocketflow.
Can you give me an example? Which parameters should I set?
from pocketflow.
Before PocketFlow, have you trained some models on this data set? What is your hyper-parameter setting, or, how do you adjust the learning rate during the training process at that time?
from pocketflow.
I mean that can I set some hyper-parameter so that PocketFlow does not call setup_lrn_rate
function?
from pocketflow.
Almost all model compression components need this function to setup the learning rate schedule and number of training iterations. I suggest you do not skip this function. If you do want to skip this, you should modify the corresponding model compression component, and manually setup the learning rate schedule.
from pocketflow.
OK,thanks
from pocketflow.
Related Issues (20)
- cifar10_channel pruned 的示例,通道剪枝(channel_pruning) 导出修改了计算图之后,速度比之前的更慢了! HOT 1
- Can the compression method provided by pocketflow be applied to MASK R-CNN? HOT 1
- QQ group HOT 1
- 我可以只用模型压缩部分么?
- TypeError: forward_train() missing 1 required positional argument: 'objects'
- Missing 1 required positional argument in constructor : data_format
- Download Pretrain Model But Get 502 Bad Gateway Error HOT 1
- You must feed a value for placeholder tensor 'model/input_1' with dtype float and shape [?,160,240,1]
- Question about export_chn_pruned_tflite_model.py HOT 1
- TF Version compatibility HOT 2
- Failed to create session
- Is it possible to compress the keras model with Pocket Flow
- Question about UniformLearner HOT 2
- Default tensorboard log output is huge
- FRCNN with VOC: Cannot batch tensors with different shapes in component 1.
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- Other issues:
- auto 通道裁剪问题
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from pocketflow.